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Given a string input, our task is to write a Python program to create a variable from that input [as a variable name] and assign it to some value. Below are the methods to create dynamically named variables from user input.
Using globals[] method to create dynamically named variables
Here we are using the globals[] method for creating a dynamically named variable and later assigning it some value, then finally printing its value.
Python3
Dynamic_Variable_Name = "geek"
globals[][Dynamic_Variable_Name] =
2020
print[geek]
Output:
2020
Using locals[] method to create dynamically named variables
Here we are using the locals[] method for creating dynamically named variable and later assigning it some value, then finally printing its value.
Python3
Dynamic_Variable_Name = "geek"
locals[][Dynamic_Variable_Name] = 2020
print[geek]
Output:
2020
Using exec[]method to create dynamically named variables
Here we are using the exec[] method for creating dynamically named variable and later assigning it some value, then finally printing its value.
Python3
Dynamic_Variable_Name = "geek"
exec["%s = %d" % [Dynamic_Variable_Name, 2020]]
print[geek]
Output:
2020
Using vars[]method to create dynamically named variables
Here we are using the vars[] method for creating dynamically named variable and later assigning it some value, then finally printing its value.
Python3
Dynamic_Variable_Name = "geek"
vars[][Dynamic_Variable_Name] = 2020
print[geek]
Output:
2020
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Python
Data Preprocessing
In this example both the values in the columns and the column names are created dynamically.
Here we dynamically create three columns that multiply the column A in our dataframe by each of the numbers in the list "multipliers".
multipliers = [2,3,4]
for i in multipliers:
df[f'times_{i}'] = df['A'] * i
df.columns
>> Index[['A', 'B', 'times_2', 'times_3', 'times_4'], dtype='object']By detro - Last Updated March 29, 2022, 7:34 p.m.
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Question :
Create new dataframe in pandas with dynamic names also add new column
I have a dataframe df
df = pd.DataFrame[{'A':['-a',1,'a'],
'B':['a',np.nan,'c'],
'ID':[1,2,2],
't':[pd.tslib.Timestamp.now[],pd.tslib.Timestamp.now[],
np.nan]}]
Added a new column
df['YearMonth'] = df['t'].map[lambda x: 100*x.year + x.month]
Now I want to write a function or macro which will do date comparasion, create a new dataframe also add a new column to dataframe.
I tried like this but seems I am going wrong:
def test[df,ym]:
df_new=df
if[ym